Evidence map›Paper›PMID 34504505›Full record

ReviewFrontiers in plant science2021

Utilizing Plant Synthetic Biology to Improve Human Health and Wellness.

Collin R Barnum, Benjamin J Endelman, Patrick M Shih

Abstract readReview
In one paragraph

Review in Frontiers in plant science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Review
  7. Article
  8. Review
  9. Article
  10. Review
  11. EngineeringACS synthetic biology · 2024
    Article
  12. Article
  13. Article
  14. Review
  15. Article
  16. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Collin R BarnumDepartment of Plant Biology, University of California, Davis, Davis, CA, United States.
Benjamin J EndelmanDepartment of Plant Biology, University of California, Davis, Davis, CA, United States.
Patrick M ShihDepartment of Plant Biology, University of California, Davis, Davis, CA, United States.

Funding

UC Davis MCB T32 Administrative Supplement to Recognize Excellence in Diversity, Equity, Inclusion, and Accessibility (DEIA) MentorshipT32GM007377 · NIGMS · UNIVERSITY OF CALIFORNIA DAVIS · PI CHEDIN, FREDERIC LOUIS · 1985 to 2023
$9.9M
Developing plant synthetic biology platforms to elucidate the role of natural productsR00AT009573 · NCCIH · UNIVERSITY OF CALIFORNIA BERKELEY · PI SHIH, PATRICK · 2018 to 2020
$704k
NCCIH NIH HHS R00 AT009573NIGMS NIH HHS T32 GM007377
6 · The paper itself

Abstract

Plants offer a vast source of bioactive chemicals with the potential to improve human health through the prevention and treatment of disease. However, many potential therapeutics are produced in small amounts or in species that are difficult to cultivate. The rapidly evolving field of plant synthetic biology provides tools to capitalize on the inventive chemistry of plants by transferring metabolic pathways for therapeutics into far more tenable plants, increasing our ability to produce complex pharmaceuticals in well-studied plant systems. Plant synthetic biology also provides methods to enhance the ability to fortify crops with nutrients and nutraceuticals. In this review, we discuss (1) the potential of plant synthetic biology to improve human health by generating plants that produce pharmaceuticals, nutrients, and nutraceuticals and (2) the technological challenges hindering our ability to generate plants producing health-promoting small molecules.

Indexed as

human healthnatural productsnutraceuticalsnutritionpharmaceuticalsplant synthetic biology

Identifiers

PMID34504505
PMCPMC8421571

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.